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    Introduction To Python Data Structure And Linear Regression

    Posted By: ELK1nG
    Introduction To Python Data Structure And Linear Regression

    Introduction To Python Data Structure And Linear Regression
    Published 8/2024
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 528.97 MB | Duration: 1h 36m

    Manipulating and analyzing python data structure in depth and understanding linear regression with associated concepts.

    What you'll learn

    Like a master chef crafting a signature dish, you'll learn to cook up python data structures from a recipe of brackets and commas.

    Delve into the spellbook of linear regression methods, which contain enchantments like `EDA`, `MISSING DATA ANALYSIS `, NORMALIZATION to manipulate data.

    Learn the incantations to safely dealing with python data structures and preventing any unintended alterations to your original creations.

    Become adept at performing magical operations such as concatenation, multiplication, and comparison to merge, replicate, and linear model in data analytics

    Requirements

    Python,IDE, Statistics, Machine Learning

    Description

    Unleash the power of python data structures and in-depth analysis of linear regression with this immersive and exciting video lesson on the Introduction to python data structure and linear regression! The tutorial covers important concepts and functions that are crucial for manipulating and analyzing data efficiently using Python.This Course  has been designed for ease and better clarity to online learners starting from how to work with a python data structure and to  perform regression operations on a data frame.From importing and exporting data to and transforming data, this course covers that are crucial for manipulating and analyzing data . We will dive into the essentials of python data structures and regression by demystifying complex concepts through clear and engaging examples.You will also learn how to perform advanced data operations such as merging, grouping, and aggregating data with ease. Unravel step-by-step examples that'll make even complex concepts a breeze to grasp, unfolding the wonders of advanced python Data structures and regression Techniques.From dazzling videos to interactive explanations, this lesson is perfect for student, professional, or data enthusiast seeking clarity on python Data structures and linear regression.Dive into the world of python Data structures with this comprehensive online tutorial, perfect for beginners looking to enhance their data analysis skills. You will positively gain a solid foundation for further exploration in the field and learn how to handle and analyze data efficiently, andBy the end of this course, you will be able to confidently work with python data frames and tackle complex data analysis tasks like a pro.So grab your pencil, sharpen your focus, and get ready to unlock the secrets of  this course that will equip you with the necessary knowledge to excel in python and data analysis tasks.

    Overview

    Section 1: Introduction to list

    Lecture 1 Introduction

    Lecture 2 List Creation

    Lecture 3 Python list overview

    Lecture 4 List access with tabulation for clarification

    Lecture 5 List Access and it's associated operations

    Lecture 6 List useful methods and its operations

    Lecture 7 List deletion with del keyword and empty list

    Lecture 8 List conversion to tuple,set and dictionary

    Section 2: Introduction to tuple

    Lecture 9 Introduction

    Lecture 10 Tuple creation

    Lecture 11 Tuple access

    Lecture 12 Iterating through a Tuple

    Lecture 13 Changing, Reassigning, and Deleting Tuples

    Lecture 14 Tuples vs. Lists

    Lecture 15 Tuple method with description

    Lecture 16 Tuple use case

    Lecture 17 Summary

    Section 3: Introduction to Set

    Lecture 18 Introduction

    Lecture 19 Example of set

    Lecture 20 Set Operations

    Lecture 21 Set Creation

    Lecture 22 Set Example

    Lecture 23 Frozen Set

    Lecture 24 Frozen set with detailed information

    Lecture 25 Frozen set usage

    Lecture 26 Summary

    Section 4: Dictionary

    Lecture 27 Introduction

    Lecture 28 Dictionary structure and examples

    Lecture 29 Accessing Elements

    Lecture 30 Accessing elements using get

    Lecture 31 Adding and Modifying Entries to a Dictionary

    Lecture 32 Removing or Deleting Elements from a Dictionary

    Lecture 33 Delete an Dictionary

    Lecture 34 Setdefault() method

    Lecture 35 Dictionary copy method

    Lecture 36 Dictionary fromkeys method

    Lecture 37 Dictionary with example and detailed content

    Lecture 38 Summary

    Section 5: Python libraries for data analysis

    Lecture 39 Introduction

    Lecture 40 Python libraries widely used for analysis machine learning and statistics

    Lecture 41 Importing libraries

    Lecture 42 Loading training data

    Lecture 43 Loading testing data

    Lecture 44 Removing Unnecessary Attributes

    Lecture 45 Correlation check

    Lecture 46 Multicollinearity

    Lecture 47 Outliers detection

    Lecture 48 Data Preprocessing

    Lecture 49 Delete Unuseful Features

    Lecture 50 Fix Datatype

    Lecture 51 Check Mising Values

    Lecture 52 Imputing missing values

    Lecture 53 Feature Engineering

    Lecture 54 Numeric Feature Scaling

    Lecture 55 Skewing with boxcox_normmax()

    Lecture 56 Adding New Features

    Lecture 57 Numerical and categorical features

    Lecture 58 Encoding Categorical Variables

    Lecture 59 One Hot Encoding

    Lecture 60 Train and test data set

    Lecture 61 Target Variable Analysis

    Lecture 62 Target Variable Transformation

    Section 6: Modeling

    Lecture 63 Cross Validation

    Lecture 64 Evaluation Metric

    Lecture 65 Linear Models

    Whether you're a novice scribe or a seasoned programmer looking to expand your repertoire, this course will have you conjuring lists with the finesse of a Pythonista.